squeeze

Remove dimensions of length 1

Syntax

B = squeeze(A)

Description

B = squeeze(A) returns an array with the same elements as the input array A, but with dimensions of length 1 removed. For example, if A is a 3-by-1-by-1-by-2 array, then squeeze(A) returns a 3-by-2 matrix.

If A is a row vector, column vector, scalar, or an array with no dimensions of length 1, then squeeze returns the input A.

Examples

3-D Array to Matrix

Create a 2-by-1-by-2 array and remove the dimension of length 1, resulting in a 2-by-2 matrix.

A = zeros(2,1,2);
A(:,:,1) = [1 2]';
A(:,:,2) = [3 4]'

A = 
A(:,:,1) =

     1
     2


A(:,:,2) =

     3
     4

B = squeeze(A)

B = 2×2

     1     3
     2     4

3-D Array to Vector

Create a 1-by-1-by-3 array and remove the dimensions of length 1, resulting in a 3-by-1 column vector.

A = zeros(1,1,3);
A(:,:,1:3) = [1 2 3]

A = 
A(:,:,1) =

     1


A(:,:,2) =

     2


A(:,:,3) =

     3

B = squeeze(A)

B = 3×1

     1
     2
     3

Input Arguments

A — Input array

multidimensional array

Input array, specified as a multidimensional array.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

This function fully supports tall arrays. For more information, see Tall Arrays.

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• Does not support cell arrays.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• Does not support cell arrays.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a